Integration of quantitative and qualitative knowledge for online decision support

Abstract EN

Modeling of time-varying resources and demands needs crucial attention in mathematical programming.

This paper presents a network flow model for three resources integrated to meet demands along a specific time period.

Both the output values of the resources and the demands are varying with time.

Storage system is used to assure high reliability of the overall system.

The proposed model is constructed as a generalized network optimization problem with imprecise coefficients.

Classical mathematical programming, alone, cannot solve such problem.

It should be combined with a rule-based system that deals with imprecise coefficients by using fuzzy variables.

The paper utilizes the simulation results together with the accompanied qualitative knowledge as a useful resource of knowledge.

A novel algorithm for machine learning is presented to acquire knowledge from the qualitative and quantitative data.

The rule-based system can be used as a decision support system that suits online problems such as renewable resources, wind water pumping, computer resources etc.